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Internal risk assessment of whole process engineering consulting consortium based on GRA-TOPSIS-FMEA
Get PDFIn order to select key risk factors, effectively control risks, and promote the smooth development of the whole process of engineering consulting consortium, Based on WBS-RBS risk identification in the whole process of engineering consulting, this paper introduces FMEA model, applies rough set and binary semantics to evaluate risk from multiple dimensions of occurrence, severity and difficulty to detect, and uses G1-improved CRITIC to calculate the comprehensive weight of risk evaluation factors, and then severity is revised based on DEMATEL. The GRA-TOPSIS model is constructed for risk ranking. Finally, the model is applied to a road network project and the analysis shows that communication and coordination risk, termination risk and schedule risk are the key risks. The model is suitable for risk assessment in the joint body and provides a feasible method for risk control in the whole process of engineering consulting consortia
The analysis of the destabilizing motion of a hyperbolic cooling tower during demolition blasting
Get PDFThe destabilizing motion characteristics of the hyperbolic cooling tower in demolition blasting are thoroughly investigated through the establishment of a numerical simulation calculation model, leading to the following conclusions regarding its destabilizing motion. The tensile-compression elastic-plastic model, which possesses the characteristics of parameter modification function and independence from unit size, can more effectively capture the mechanical properties of concrete materials and find better application in the simulation and calculation research of reinforced concrete structures. The self-oscillation frequency check and collapse morphological analysis are employed to validate the accuracy of the simulation calculation model for hyperbolic cooling towers, as well as to assess the rationality of parameters in the tensile-compression elastic-plastic model. The collapse of a cooling tower induces flexural deformation in the lateral wall, tensile disturbance in the upper and middle sections of the cylinder, and compressive disturbance in the vertical cross-section. The cylinder body has incurred damage as a result of the tower wall’s front end striking the ground at the directional window position on the front side of the throat, leading to a significant extrusion deformation issue. The buckling deformation in the central and lower sections of the rear wall propagated towards the back side of the tower wall upon reaching the ground, ultimately resulting in an “inverted V-shaped” damage along the buckling deformation line. The research findings hold significant relevance for future endeavors
Cross domain fault diagnosis method based on MLP-mixer network
Get PDFThe quality of rolling bearings determines the safety of mechanical equipment operation, and bearings with more precise structures are prone to damage due to excessive operation. Therefore, cross domain fault diagnosis of bearings has become a research hotspot. To better improve the accuracy of bearing cross domain fault diagnosis, this study proposes two models. One is a cross domain feature extraction model constructed using a mixed attention mechanism, which recognizes and extracts high-level features of bearing faults through channel attention and spatial attention mechanisms. The other is a bearing cross domain fault diagnosis model based on multi-layer perception mechanism. This model takes the feature signals collected by the attention mechanism model as input to identify and align the differences between the source and target domain features, facilitating cross domain transfer of features. The experimental results show that the mixed attention mechanism model has a maximum accuracy of 97.3 % for feature recognition of different faults, and can successfully recognize corresponding signal values. The multi-layer perception model can achieve the highest recognition accuracy of 99.5 % in bearing fault diagnosis, and it can reach a stable state when it iterates to 26, and the final stable loss value is 0.28. Therefore, the two models proposed in this study have good application value
Prediction and evaluation of polymer turbulent drag reduction efficiency based on BP neural network
Get PDFIn the process of oil exploitation and transportation, in order to effectively predict and control energy consumption for drag reduction of oil flow, in this paper a BP neural network was proposed based method for predicting and evaluating the turbulent drag reduction efficiency of polymers, which can greatly improve the current situation of relying on empirical formulas and low generality in polymer turbulent drag reduction efficiency prediction. Based on the experimental data sets of four commercial polymer drag-reducing agents FLOXL, М-Flowtreat, Necadd-447, and FLO MXA, obtained at different polymer concentrations, viscosity, density, and Reynolds number, a BP neural network has been established and the optimal number of neurons in the hidden layer was selected using the root mean square error (RMSE) value to obtain the optimal BP neural network prediction model. The BP neural network prediction models for the four polymer drag-reducing agents all have a good fit of 0.98 or above, and the R2 of the trained BP neural network for the Necadd-447 drag-reducing agents is 0.9949, which is the best among the four polymer drag-reducing agents. The BP neural network established in this paper can be applied to the turbulent drag reduction transport of long-distance pipelines for oil products to achieve the prediction of the drag reduction efficiency of polymer additives
Design of automotive mechanical automatic transmission system based on torsional vibration reduction
Get PDFAutomatic transmission system is the core part of vehicle transmission processing, which can improve driving safety. In order to improve the shift effect of automotive automatic mechanical transmission and narrow the gap between the vehicle speed and the expected speed, an automotive automatic mechanical transmission system based on torsional damping was designed in the experiment. On the basis of hardware composed of different modules and fuzzy control algorithm, the system realizes the software design of vehicle automatic mechanical transmission system. The experimental results show that when the system is applied in practice, the gear selection time of the vehicle is between 0.2 s-0.3 s, and the gear shift time is between 0.3 s-0.4 s. The gap between the vehicle speed and the expected speed, and between the vehicle speed and the expected speed is small. The practical application effect is good
Sensitivity analysis of numerical model parameters for optimized PEH responses
Get PDFWith the increasing popularity of wearable devices, typically employed in fitness and health monitoring, there is an evident need to extend their autonomy and replace the conventional power sources with environmentally friendly alternatives. Piezoelectric energy harvesting systems, optimized for collecting kinetic energy from random human motion and transduce it into electrical energy, represent a viable option for powering autonomous wearables. Since established analytical methods are unable to model the behaviour of piezoelectric harvesters with complex optimized geometries, suitable numerical models need to be employed for their design. This implies the need of a thorough study focused on the mechanical engineering design optimization purposes of how the finite element type and mesh density affect the uncoupled modal and coupled transient responses of a new class of optimised design configurations of the studied devices
Fault diagnosis and analysis of hydraulic brake based on friction vibration signal
Get PDFThe friction vibration signal corresponding to different fault types of brakes is significantly different, thus a hydraulic disc brake fault diagnosis and judgment scheme based on vibration signal detection was proposed and validated in the paper. According to the composition and electric control principle of hydraulic brake, the vibration signal detection and brake pressure control strategies were established. The key hardware and isolation circuit of the detection system were designed, which can effectively improve the stability and anti-interference ability in the process of vibration data acquisition and transmission with SPI and CAN bus communication scheme. In order to eliminate noise interference in friction vibration signal and improve the accuracy of fault diagnosis with advantage, wavelet threshold denoising method was applied to brake disc vibration signal processing. The denoised signal can be obtained by inverting the selected wavelet coefficients to separate the useful components of the signal from the invalid noise. For the research on the correlation between fault types and vibration signal characteristics, a friction vibration test bench for hydraulic braking system was built to obtain and process the output signal from vibration sensor. The frequency spectrum response laws of vibration signals were compared and analyzed when the brake disc was normal and had surface defects, including microcracks, excessive wear and fatigue peeling. The external parameters such as brake pressure and spindle speed were keeping constant, thus eliminating the influence of working factors on vibration characteristics. In order to study the influence of brake pressure failure on friction vibration, the variation law of vibration signal is compared and analyzed under the condition of hydraulic valve leakage and pressure maintaining failure. The results show that the friction vibration signal can be used as an effective basis for judging the surface defects and brake pressure faults of brake discs. Under the condition of wavelet threshold denoising, accurate and effective vibration parameters can be obtained, which is of great significance to the safety and reliability of the braking system
Mechanical behavior of a highway tunnel under the influence of lining crack disease
Get PDFHighway tunnels built in China in the early years of operation have different forms of diseases, which have a great impact and threat to the normal operation and safety of the tunnel. To ensure the safety and stability of the lining structure, this paper analyzes the mechanical behavior of the lining structure under the influence of the disease and reveals the evolution law of the lining crack disease for typical tunnel lining cracks. The results of the study show that only the circumferential and longitudinal stresses at the vault increase when cracks exist in the inner wall of the lining vault. The longitudinal cracks in the inner wall of the lining have the greatest influence on the lining stress state
Configuration design and load capacity analysis of pelvic fracture reduction robot
Get PDFRobot-assisted reduction of pelvic fracture requires large workspace and large load capacity. A kind of six degree-of-freedom (DOF) robot for pelvic fracture reduction is designed, which is a hybrid configuration composed of three-revolute-revolute-revolute (3RRR) parallel mechanism and three-dimensional guide rail. The hybrid configuration can ensure that the robot meet the needs of large workspace and large load capacity. Through the comparative analysis of dynamic and virtual prototype simulation, the reduction force of the designed reduction robot can reach 200 N. The experimental results show that the robot not only has the characteristics of high precision and high load of parallel robot, but also has the characteristics of large workspace of series robot
Carbon deposition fault diagnosis of small piston engine based on optimized VMD
Get PDFAiming at the small piston engine carbon deposition fault in the process of running, based on the cylinder pressure and cylinder head vibration signal of the engine, a fault diagnosis method combining variational mode decomposition and support vector machine is used to diagnose the engine carbon deposition fault. Firstly, particle swarm optimization algorithm is used to optimize the parameters of the variational mode decomposition. Then, the intrinsic mode function is obtained by processing the pressure signal and cylinder head vibration signal of the engine. Then, the singular spectrum entropy is calculated by singular value decomposition of the intrinsic mode function. Finally, the singular spectrum entropy is input into the support vector machine classifier as the feature data set for training and testing. The results show that this method can identify the carbon deposition fault of the starting motor well, and the accuracy of fault identification and classification of cylinder pressure and cylinder head vibration signal is 98.33 % and 99.17 % respectively, which verifies the effectiveness of this method